Year: 2009
Type: article
Abstract: In this paper, multilevel genetic algorithm (MLGA) is presented to solve the optimization of surface mounted permanent magnet synchronous machine (SPMSM), which has features of mixed continuous and discrete design variables, multi-modal objective functions, etc. Firstly, the multilevel optimization problem is described by using the problem matrix. The values in the problem matrix are deduced by correlation analysis. Secondly, the architecture and implementation of MLGA are carried out. Thirdly, the new algorithm is applied to a bilevel optimization of SPMSM to verify this multilevel optimization. The results compared with those of traditional genetic algorithm (GA) and discussions of the multilevel optimization are presented.
Source: IEEE Transactions on Magnetics
Authors: Shuhong Wang, Xiangjun Meng, Ningning Guo, Haibo Li, Jie Qiu, Jian Guo Zhu, Youguang Guo, Dikai Liu, Yi Wang, Wei Xu
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W2103177343